Top Remote Machine Learning Jobs in Pittsburgh, PA

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The Machine Learning Architect will design and implement ML solutions on cloud platforms, working directly with customers to align strategies with business goals. Responsibilities include end-to-end project management, model deployment, and maintaining strong customer relationships.

Lead the fraud strategy to protect customers and card portfolios, develop real-time models with Data Science, and manage fraud performance metrics. Collaborate across teams to implement effective fraud controls and optimize processes.

The Global Strategic Feasibility Analytics Lead develops feasibility data analytics initiatives, transforms data into insights, collaborates with stakeholders, and drives data-driven decision-making for study planning.

The Staff Analytics Engineer builds data workflows, ensures data integrity, resolves customer issues, and develops insights products, leveraging SQL and Python skills.

Lead the Anaplan platform and data strategy, develop financial models, implement advanced analytics, and mentor team members for a FinTech team.

Lead a data science and analytics team for Netflix's game product and platform. Responsible for measurement, experimentation strategies, and coaching the team to deliver insights vital for games strategy.

Lead data acquisition and management strategies for AI models, analyze data systems, oversee partnerships, and guide a team in optimized data usage.

This role involves training AI models in Energy and Power by providing feedback on outputs, problem-solving, and identifying biases in the AI's knowledge base.

As an AI Tutor, you will teach, evaluate, and red-team AI models in data science principles, focusing on statistical modeling, machine learning, and data ethics.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

The Machine Learning Engineer develops AI solutions for cancer care using expertise in ML algorithms and genomic data, collaborating across teams.

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

As a Senior Data Scientist, you will develop models to extract insights from complex datasets, focusing on temporal and geospatial features, while collaborating with engineering teams to implement solutions.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.